Manufacturing Analytics Engineer - IE Systems & Modeling

ZENITH INFOTEK LLC; Pittsburgh (Allegheny County); On-site; USD 80,000 - 120,000; Full time

Benefits offered by this job

Competitive salary

Opportunity for advancement

Training & development

Job summary

ZENITH INFOTEK LLC is seeking an Industrial Engineering Analytics Engineer for its Pittsburgh facility. This role focuses on enhancing manufacturing efficiency through advanced analytical models, involving tight collaboration across operations.

The successful candidate should possess strong industrial engineering fundamentals and expertise in analytics, simulation, and AI-driven systems, making pivotal contributions to large-scale manufacturing environments. A competitive salary, opportunities for advancement, and professional training will be provided.

Qualifications

• Strong analytical and problem-solving skills are essential.
• Ability to build scalable models and analytics systems.
• Experience in cross-functional team collaboration is a plus.

Responsibilities

• Lead analytical model development to enhance manufacturing efficiency.
• Manage integrated IE models connecting various operational factors.
• Support decision-making with data-driven insights.

Skills

Greenfield or brownfield project experience

Equipment planning

Capacity planning

Labour planning

CAPEX management

Supplier validation

Capital investments – ROI, IRR, NPV

Design and maintain OEE models

Support factory ramp-up

Material planning

PFMEA

Lean Manufacturing

Six Sigma

Simulation tools experience

Strong expertise in Excel

Knowledge of AI-driven tools

Education

Bachelor's degree in Industrial Engineering or relevant field

Tools

Excel advanced modeling

Python

SQL

Power BI/Tableau

FlexSim, AnyLogic, Simio (simulation tools)

Job description

ZENITH INFOTEK LLC is seeking an Industrial Engineering Analytics Engineer for its Pittsburgh facility. This role focuses on enhancing manufacturing efficiency through advanced analytical models, involving tight collaboration across operations.

The successful candidate should possess strong industrial engineering fundamentals and expertise in analytics, simulation, and AI-driven systems, making pivotal contributions to large-scale manufacturing environments. A competitive salary, opportunities for advancement, and professional training will be provided.